I am aware that the error is related to the broadcasting, and that it can be solved by matching the shape of x to that of y --- this is how I solved it in the first place. I was thinking that the function "promises" to integrate over an array given a x vector and the axis, so let obscure the broadcasting rules and just enable it to do the work. There is a reason to leave trapz as it is (or even drop it) since numpy should stay as close as possible to "bare metal", but this function is borrowed also by scipy integration package, thus I rather give it a face lift.
Nadav.
-----הודעה מקורית-----
מאת: numpy-discussion-bounces@scipy.org בשם Ryan May
נשלח: ש 12-יולי-08 22:24
אל: Discussion of Numerical Python
נושא: Re: [Numpy-discussion] A correction to numpy trapz function
Nadav Horesh wrote:
> Here is what I get with the orriginal trapz function:
>> IDLE 1.2.2
>>>> import numpy as np
>>>> np.__version__
> '1.1.0'
>>>> y = np.arange(24).reshape(6,4)
>>>> x = np.arange(6)
>>>> np.trapz(y, x, axis=0)
>> Traceback (most recent call last):
> File "<pyshell#4>", line 1, in <module>
> np.trapz(y, x, axis=0)
> File "C:\Python25\Lib\site-packages\numpy\lib\function_base.py", line 1536, in trapz
> return add.reduce(d * (y[slice1]+y[slice2])/2.0,axis)
> ValueError: shape mismatch: objects cannot be broadcast to a single shape
>(Try not to top post on this list.)
I can get it to work like this:
import numpy as np
y = np.arange(24).reshape(6,4)
x = np.arange(6).reshape(-1,1)
np.trapz(y, x, axis=0)
From the text of the error message, you can see this is a problem with
broadcasting. Due to broadcasting rules (which will *prepend*
dimensions with size 1), you need to manually add an extra dimension to
the end. Once I resize x, I can get this to work. You might want to
look at this: http://www.scipy.org/EricsBroadcastingDoc
Ryan
--
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
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